In non-probability sampling (also known as non-random sampling) not all members of the population has a chance of participating in the study. This is contrary to probability sampling, where each member of the population has a known, non-zero chance of being selected to participate in the study.
Necessity for non-probability sampling can be explained in a way that for some studies it is not feasible to draw a random probability-based sample of the population due to time and/or cost considerations. In these cases, sample group members have to be selected on the basis of accessibility or personal judgment of the researcher. Therefore, the majority of non-probability sampling techniques include an element of subjective judgement. Non-probability sampling is the most helpful for exploratory stages of studies such as a pilot survey.
The issue of sample size in non-probability sampling is rather ambiguous and needs to reflect a wide range of research-specific factors in each case. Nevertheless, there are some considerations about the minimum sample sizes in non-probability sampling as illustrated in the table below:
|Nature of study||Minimum sample size|
|Semi-structured, in-depth interviews||5 – 25|
|Ethnographic||35 – 36|
|Grounded theory||20 – 35|
|Considering a homogeneous population||4 – 12|
|Considering a heterogeneous population||12 – 30|
Minimum non-probability sample size
The following is the list of the most popular non-probability sampling methods:
- Judgement Sampling
- Quota Sampling
- Convenience Sampling
- Extensive Sampling
Advantages of Non-Probability Sampling
- Possibility to reflect the descriptive comments about the sample
- Cost-effectiveness and time-effectiveness compared to probability sampling
- Effective when it is unfeasible or impractical to conduct probability sampling
Disadvantages of Non-Probability Sampling
- Unknown proportion of the entire population is not included in the sample group i.e. lack of representation of the entire population
- Lower level of generalization of research findings compared to probability sampling
- Difficulties in estimating sampling variability and identifying possible bias
My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach contains a detailed, yet simple explanation of sampling methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in this e-book in simple words.
 Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited
Sampling Methods Essay
2036 Words9 Pages
Sampling is the framework on which any form of research is carried out. A suitable sample that meets the inclusion and exclusion criteria of a research design must be chosen from a given population to carry out studies. In this essay comparison is made between stratified random sampling and convenience sampling. The population on which the researcher is interested in carrying out his or her research may be too large, therefore a suitable sample which can represent the population in correct proportion must be chosen. Restraints such as limitation of time, resources and many other factors necessitate the selection of a sample for research purpose so that better quality data is obtained from it and that the researcher can make statement about…show more content…
The methodological strength and weaknesses of this two sampling methods is discussed in terms of identifying the samples for research, the representativeness it possesses to the general population, the methods and the outcome.
Stratified random sampling is a probability sampling where the selection of sampling unit is left to a random process, all units in the sample has an equal and non-zero chance of being selected on a probability ground or chance and not on the choice or judgement of the researcher (Sim,J and Wright,C. 2000,). Convenience sampling is an example of non probability sampling where the selection of the units is not by chance, rather it is dependent on the researcher’s judgement, the researcher decides the samples to be included in the study which may be subject to availability, time, individual preferences etc. The probability of selection of a particular sampling unit may or may not be known.
Stratified random sampling is commonly done in quantitative researches. When the samples reflect the characteristics of the target population in the same proportion; assumptions can be made on generalizing the data acquired from these samples provided it has been done correctly, since it is statistically representative (Sim,J and wright,C.,2000) but sampling error